Speech decoding systems are known and widely used. However, conventional speech decoding systems are limited in their applicability due to the enormous amount of processing demands placed on such conventional systems and/or the user specific nature of some of these systems.
More particularly, many conventional speech decoding systems include an acoustic processing circuit for converting to a digital electrical signal, a spoken utterance (e.g. speech in the form of a word, phrase or sentence, as picked up by a microphone). Some of these systems utilize a phonetic encoder to convert the digital signals representing the utterance into a sequence of phoneme codes. Each phoneme is the smallest unit of speech that can be used to distinguish one sound from another. The sequence of phoneme codes is decoded into a literal string of words using a phonetic dictionary and a syntax file. The phonetic dictionary correlates phoneme code sequences to words. The syntax file contains a number of production rules that define an allowable grammatical structure and limit the words that can be recognized in different parts of the grammatical structure.
The use of the syntax file increases the efficiency of the phonetic decoding process. However, systems employing such still have problems with both speed and accuracy due to the large size of the syntax file employed. In other words, the speed and accuracy of the system decreases as the size and complexity of the syntax file increases.
Another type of speech decoding system utilizes a template matching algorithm that compares a digital representation of an aural signature (e.g., analog waveform representation of detected speech) to a database of word signatures and selects the closest match. This type of system requires unnatural pauses between words so that the system can distinguish when a word begins and ends. This system also requires an intended user to speak the same words repeatedly so that the system can obtain numerous waveform samples representing the same word. Not only is this process extremely time-consuming and tiresome, but it also makes the system user specific. Furthermore, like most other prior speech decoding systems as the size of the database increases errors in decoding occur more frequently and the speed of this system decreases.
Thus, the aforementioned speech decoding systems are generally not suitable for employment in communication systems having wireless mobile communication units which communicate using an optical or radio link with a hardwired network, such as a local area network (LAN). More specifically, market forces are requiring that these wireless mobile communication units become smaller, lighter and be faster in response to user inputs. Consequently, space is at a premium in such devices as well as the amount of data that must be processed by such devices in order to maximize response time to a user input and battery life.
Retail stores and warehouses, for example, may use such communication systems to track inventory, replenish stock or provide for efficient customer shopping (e.g., in a grocery store). Customers may enter and retrieve information using the mobile communication units which can be carried through the store. In manufacturing facilities, such systems are useful for tracking parts, completed products and defects. In a medical environment, these systems can reduce the time needed to fill out forms and eliminate inaccuracies by allowing medical personnel to transmit data directly from a mobile communication unit carried by the medical personnel.
However, the aforementioned speech decoding systems are not suitable for employment in such wireless communication systems largely because of the extensive data processing required by such systems. Moreover, in a wireless communication system it is often desired for the mobile communication units to be used by a number of individuals (e.g., different shoppers). Therefore, speech decoding systems which need to be trained to recognize a particular user's speech patterns (e.g., user specific) are not appropriate for mobile communication units which may be used by numerous individuals.
Thus, there is a strong need in the art for a speech decoding system which has low data processing requirements and may be used by numerous individuals so as to be suitable for use in a communication system using mobile communication units.